1. Field of the Invention
The present invention relates to the field of computer-based processes. Specifically, the present invention relates to a method for auction-based simulation to extract a demand curve.
2. Related Art
Modern electronic forum based auctions, such as World Wide Web and other Internet based auctions have complex rules with varied and partially observable bidder characteristics and behaviors. Analytical derivation of key bidder characteristics, for example, consumer willingness to pay, and prediction of auction outcomes, for example, seller's revenue, from limited and partially observed bidder data has been very difficult.
Conventional solutions to these problems are analytical, requiring mathematical, symbolic evaluation of simple auction designs and bidder characteristics. Such solutions, when available, are computationally slow and allow adequate and direct human interpretation of their results. However, such solutions are not always available for all auction situations.
Such solutions also have a disadvantage in that they require extraordinary skill and time to develop them. Further, conventional methods fail to deal with more complex auctions. And even if analytical solutions expressed in closed form formulas or equations are found for certain auction rules, it is unlikely that these would be applicable to new, or even slightly changed auction rules or formats.
What is needed is a method that can provide a simulation based method for analyzing new auction formats and rules, from limited and partially observable bidder characteristics and by utilizing any known results on some aspects of the new auction rules. What is also needed is a simulation platform that is general enough to be easily modified to a specific design of auctions. Further, what is needed is a method that can utilize known results on some aspects of the auction rules under consideration, and simultaneously recover an extended set of bidder characteristics from limited and partially observed, existing bidder data, and that can predict bidder behavior under the new auction rules.